You are not logged in.

A survey of recommendation techniques based on offline data processing

Ren, Yongli, Li, Gang and Zhou, Wanlei 2015, A survey of recommendation techniques based on offline data processing, Concurrency computation: practice and experience, vol. 27, no. 15, pp. 3915-3942, doi: 10.1002/cpe.3370.

Attached Files
Name Description MIMEType Size Downloads

Title A survey of recommendation techniques based on offline data processing
Author(s) Ren, Yongli
Li, GangORCID iD for Li, Gang orcid.org/0000-0003-1583-641X
Zhou, WanleiORCID iD for Zhou, Wanlei orcid.org/0000-0002-1680-2521
Journal name Concurrency computation: practice and experience
Volume number 27
Issue number 15
Start page 3915
End page 3942
Total pages 28
Publisher Wiley
Place of publication London, Eng.
Publication date 2015-10
ISSN 1532-0626
1532-0634
Keyword(s) Science & Technology
Technology
Computer Science, Software Engineering
Computer Science, Theory & Methods
Computer Science
recommendation
collaborative filtering
recommender systems
OF-THE-ART
POSSIBLE EXTENSIONS
SYSTEMS
MAJORITY
SETS
Summary Recommendations based on offline data processing has attracted increasing attention from both research communities and IT industries. The recommendation techniques could be used to explore huge volumes of data, identify the items that users probably like, translate the research results into real-world applications and so on. This paper surveys the recent progress in the research of recommendations based on offline data processing, with emphasis on new techniques (such as temporal recommendation, graph-based recommendation and trust-based recommendation), new features (such as serendipitous recommendation) and new research issues (such as tag recommendation and group recommendation). We also provide an extensive review of evaluation measurements, benchmark data sets and available open source tools. Finally, we outline some existing challenges for future research.
Language eng
DOI 10.1002/cpe.3370
Field of Research 0805 Distributed Computing
0803 Computer Software
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Wiley
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081077

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in TR Web of Science
Scopus Citation Count Cited 3 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 151 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Fri, 26 Feb 2016, 11:34:42 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.